Algorithm of locally weighted regression is presented in this contribution. Local approximator repeatedly uses the locally linear model based on least square method. Simu [...]

The paper proposes an approach to modeling of systems with a parametric uncertainty. The approach is based on use of upper linear fractional transformation which is commo [...]

Control design of rotating shaft levitated by active magnetic bearing is described in this contribution. Genetic algorithm is used to design controller parameters. Depend [...]

The problems of analysis, modelling and simulation of drive systems are solved on Institute of Mechanics of Solids for over 20 years. During that time period not only the [...]

Q-learning method proved to be usable in active magnetic bearing (AMB) control task, however the learning speed remains the main problem. Two-phase variant of the Q-learn [...]

The possible method of walking policy obtaining of four-legged robot through Q-learning is discussed in the contribution. Q-learning is implemented using architecture rep [...]

The leg design is described in the contribution. Some possibilities of leg control and requirements related to both sensor system of the leg and complete robot are assign [...]

Locally Weighted Learning (LWR) is a class of approximations, based on a local model. In this paper we demonstrate using LWR together with Q-learning for control tasks. Q [...]

The creation of direct kinematic model is relatively simply in contrast with creation of analytic inverse model. With using of approximating methods is inverse modelling [...]

Abstrakt: Příspěvek se zabývá řešením otázky navigace autonomního lokomočního robotu (ALR) OMR III. Dalším úkolem bylo vytvořením navigačních modulů p [...]